_maybe_get_mask(values: 'np.ndarray', skipna: 'bool', mask: 'npt.NDArray[np.bool_] | None') -> 'npt.NDArray[np.bool_] | None'
This function will compute a mask iff it is necessary. Otherwise, return the provided mask (potentially None) when a mask does not need to be computed.
A mask is never necessary if the values array is of boolean or integer dtypes, as these are incapable of storing NaNs. If passing a NaN-capable dtype that is interpretable as either boolean or integer data (eg, timedelta64), a mask must be provided.
If the skipna parameter is False, a new mask will not be computed.
The mask is computed using isna() by default. Setting invert=True selects notna() as the masking function.
input array to potentially compute mask for
boolean for whether NaNs should be skipped
nan-mask if known
Compute a mask if and only if necessary.
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